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WO2025198816A1 - Procédés et systèmes de suivi de rotule - Google Patents

Procédés et systèmes de suivi de rotule

Info

Publication number
WO2025198816A1
WO2025198816A1 PCT/US2025/017488 US2025017488W WO2025198816A1 WO 2025198816 A1 WO2025198816 A1 WO 2025198816A1 US 2025017488 W US2025017488 W US 2025017488W WO 2025198816 A1 WO2025198816 A1 WO 2025198816A1
Authority
WO
WIPO (PCT)
Prior art keywords
patella
data points
flexion
femur
circle
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2025/017488
Other languages
English (en)
Inventor
Milad KHASIAN
Nathan A. NETRAVALI
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Smith and Nephew Orthopaedics AG
Smith and Nephew Inc
Original Assignee
Smith and Nephew Orthopaedics AG
Smith and Nephew Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Smith and Nephew Orthopaedics AG, Smith and Nephew Inc filed Critical Smith and Nephew Orthopaedics AG
Publication of WO2025198816A1 publication Critical patent/WO2025198816A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4538—Evaluating a particular part of the muscoloskeletal system or a particular medical condition
    • A61B5/4585—Evaluating the knee
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories

Definitions

  • the present disclosure relates generally to orthopedic apparatuses and methods to aid in treating knee related injuries and disease. More specifically, the present disclosure relates to patella tracking for assistance in knee replacement operations.
  • Knee arthroplasty commonly known as knee replacement surgery, is a procedure designed to relieve pain and restore function in diseased knee joints.
  • the surgery involves removing damaged cartilage and bone from the surface of the knee joint and replacing them with artificial components made of metal alloys, high-grade plastics, and polymers.
  • This procedure is typically recommended for patients with severe osteoarthritis, rheumatoid arthritis, or traumatic injury to the knee.
  • the goal is to alleviate pain, improve mobility, and enhance the overall quality of life for individuals who have not responded to other treatments such as medications, physical therapy, or less invasive surgeries.
  • TKA total knee arthroplasty
  • patellofemoral related issues the focus has been almost exclusively on the tibiofemoral joint, with minimal attention to the patellofemoral joint.
  • PFJ patellofemoral joint
  • Patellar maltracking can lead to multiple adverse conditions, such as extensor mechanism deficiency and patellofemoral dysfunction. Accordingly, avoiding patellar maltracking is one of the goals of TKA procedure.
  • patella tracking intra-operatively Conventional methods to assess patella (or PFJ) tracking intra-operatively are limited and have evolved little since they were first introduced.
  • the predominant methods to evaluate patella tracking intra-operatively involve the surgeon passively flexing the knee and observing if the patella dislocates, subluxes, or tilts, either with or without trials or final components.
  • Another technique for intraoperative assessment of patellar tracking is performed after reduction of the patella and involves taking the knee through the full flexion arc without closing the medial arthrotomy and without a medial force from the thumb to keep the patella located.
  • Such methods have been modified with the addition of a single stitch to the medial arthrotomy in which extensor mechanism balance was stated to be achieved if the patella did not tilt, subluxate, or dislocate during flexion.
  • Robotic tools offer a potential avenue for surgeons to gauge and control patellofemoral tracking during TKA procedures. Although the assessment of dynamic patellar motion using robotic tools has been explored in cadaveric models, their integration into clinical practice has been hindered by practical and technical obstacles. As such, there is a need for improved systems, including robot-assisted tools to assess patella tracking intra-operatively.
  • the present disclosure relates to a method for patella tracking, for example, before and/or after a knee replacement operation.
  • the method includes accessing, by a computing device, a surface model of a femur.
  • the method includes collecting, using a sensor in communication with the computing device, a set of first data points defining a first movement of a patella during a first flexion of a knee joint of the femur.
  • the method includes collecting, using the sensor, a set of second data points defining a second movement of the patella during a second flexion of the knee joint.
  • the method includes mapping, by the computing device, a first pathway and a second pathway of the patella on the surface model of the femur, the first pathway being defined by the set of first data points and the second pathway being defined by the set of second data points. In some examples, the method includes determining, by the computing device and based on the first pathway and the second pathway of the patella, first patella motion components and second patella motion components of the patella. In some examples, the method includes comparing, by the computing device, the first patella motion components to the second patella motion components to determine a deviation in a motion of the patella.
  • the method includes determining, by the computing device and based on the deviation and the surface model of the femur, a corrective action to minimize the deviation in the motion of the patella. In some examples, the method includes outputting, by the computing device, an instruction for performing the corrective action.
  • the method further includes collecting, using the sensor, mapping data that depicts a surface of the femur and generating, by the computing device, the surface model of the femur using the mapping data.
  • collecting the set of first data points and the set of second data points using the sensor includes identifying, by the computing device from data collected by the sensor, at least one point on the patella; and collecting, by the computing device using the sensor, movement data of the at least one point on the patella, wherein the set of first data points includes movement data of the at least one point during the first flexion and the set of second data points includes movement data of the at least one point during the second flexion.
  • the senor is attached to the patella; and collecting the set of first data points and the set of second data points using the sensor includes the computing device using a motion capture device to detect motion of the sensor, and thereby the patella, as the sensor moves with the patella during the first flexion and the second flexion.
  • determining the first patella motion components include fitting, by the computing device, a first plane to the set of first data points, wherein the first plane is defined by a centroid of the set of first data points and a normal vector that is perpendicular to a direction of the set of first data points.
  • the method further includes projecting, by the computing device, the set of first data points onto the first plane; and fitting, by the computing device, a first circle to the projected set of first data points.
  • a center of the first circle defines a first patella center of rotation (PCOR) of the patella during the first flexion.
  • PCOR patella center of rotation
  • a first axis passing through the center of the first circle in a direction of the first plane's normal vector defines a first patella flexion axis relative to a femur trochlea of the femur, during the first flexion.
  • the first patella motion components include the first PCOR and the first patella flexion axis.
  • determining the second patella motion components includes fitting, by the computing device, a second plane to the set of second data points, wherein the second plane is defined by a centroid of the set of second data points and a normal vector that is perpendicular to a direction of the set of second data points.
  • the method further includes projecting, by the computing device, the set of second data points onto the second plane.
  • the method further includes fitting, by the computing device, a second circle to the projected set of second data points. In some examples, a center of the second circle defines a second PCOR of the patella during the second flexion.
  • a second axis passing through the center of the second circle in a direction of the second plane's normal vector defines a second patella flexion axis relative to the femur trochlea of the femur, during the second flexion.
  • the second patella motion components include the second PCOR and the second patella flexion axis.
  • the method further includes displaying, by the computing device on a graphical user interface, the surface model of the femur with one or more of the first circle, the second circle, the first plane, the second plane, the set of first data points, the set of second data points, the center of the first circle, the center of the second circle, the first patella flexion axis, and the second patella flexion axis projected thereon.
  • comparing the first patella motion components to the second patella motion components to determine the deviation includes one or more of comparing, by the computing device, a radius of the first circle to the radius of the second circle to determine the deviation; comparing, by the computing device, a center of the first PCOR of the patella to the second PCOR of the patella to determine the deviation; comparing, by the computing device, the first plane to the second plane to determine the deviation; and comparing, by the computing device, a first extension point and a first flexion point from the set of first data points to a second extension point and a second flexion point from the set of second data points to determine the deviation.
  • the set of first data points is captured prior to a surgical replacement of the knee joint and the set of second data points is captured during a trialing stage of the surgical replacement of the knee joint.
  • the corrective action includes one or more of adjusting a polyethylene thickness of an implant of the knee joint; performing a tibial rotation; making a positional adjustment to the implant; making an additional cut of a bone; and performing a soft tissue release.
  • outputting the instruction for performing the corrective action includes one or more of displaying a graphical user interface (GUI) element on a display to indicate an adjustment to the polyethylene thickness of the implant, a direction of movement of the tibia, a direction of movement of the implant, or a location of the soft tissue release; outputting a control signal to a robot to implement at least a portion of the corrective action; and generating second instructions, including an indication of a location and a size of a cut to the femur, and sending or displaying the second instructions.
  • GUI graphical user interface
  • a system for tracking a patella includes a processing circuit in communication with a sensor.
  • the system further includes a memory storing executable instructions that, when executed by the processing circuit, configure the system to perform various operations.
  • the system is configured to access a surface model of a femur.
  • the system is configured to collect, using the sensor, a set of first data points defining a first movement of a patella during a first flexion of a knee joint of the femur.
  • the system is configured to collect, using the sensor, a set of second data points defining a second movement of the patella during a second flexion of the knee joint.
  • the system is configured to map a first pathway and a second pathway of the patella on the surface model of the femur, the first pathway being defined by the set of first data points and the second pathway being defined by the set of second data points. In some examples, the system is configured to determine, based on the first pathway and the second pathway of the patella, first patella motion components and second patella motion components of the patella. In some examples, the system is configured to compare the first patella motion components to the second patella motion components to determine a deviation in a motion of the patella. In some examples, the system is configured to determine, based on the deviation and the surface model of the femur, a corrective action to minimize the deviation in the motion of the patella. In some examples, the system is configured to output an instruction for performing the corrective action.
  • the executable instructions further configure the system to collect, using the sensor, mapping data that depicts a surface of the femur; and generate the surface model of the femur using the mapping data.
  • collecting the set of first data points and the set of second data points using the sensor includes the system being configured to identify, from data collected by the sensor, at least one point on the patella; and collect, using the sensor, movement data of the at least one point on the patella, wherein the set of first data points includes movement data of the at least one point during the first flexion and the set of second data points includes movement data of the at least one point during the second flexion.
  • the senor is attached to the patella.
  • collecting the set of first data points and the set of second data points using the sensor includes the system being configured to use a motion capture device to detect motion of the sensor, and thereby the patella, as the sensor moves with the patella during the first flexion and the second flexion.
  • determining the first patella motion components include the system being configured to fit a first plane to the set of first data points, wherein the first plane is defined by a centroid of the set of first data points and a normal vector that is perpendicular to a direction of the set of first data points.
  • the system is further configured to project the set of first data points onto the first plane; and fit a first circle to the projected set of first data points.
  • a center of the first circle defines a first patella center of rotation (PCOR) of the patella during the first flexion.
  • PCOR patella center of rotation
  • a first axis passing through the center of the first circle in a direction of the first plane's normal vector defines a first patella flexion axis relative to a femur trochlea of the femur, during the first flexion.
  • the first patella motion components include the first PCOR and the first patella flexion axis.
  • determining the second patella motion components include the system being configured to fit a second plane to the set of second data points, wherein the second plane is defined by a centroid of the set of second data points and a normal vector that is perpendicular to a direction of the set of second data points.
  • the system is further configured to project the set of second data points onto the second plane; and fit a second circle to the projected set of second data points.
  • a center of the second circle defines a second PCOR of the patella during the second flexion.
  • a second axis passing through the center of the second circle in a direction of the second plane's normal vector defines a second patella flexion axis relative to the femur trochlea of the femur, during the second flexion.
  • the second patella motion components include the second PCOR and the second patella flexion axis.
  • the executable instructions further configure the system to display, on a graphical user interface, the surface model of the femur with one or more of the first circle, the second circle, the first plane, the second plane, the set of first data points, the set of second data points, the center of the first circle, the center of the second circle, the first patella flexion axis, and the second patella flexion axis projected thereon.
  • comparing the first patella motion components to the second patella motion components to determine the deviation includes the system being configured to execute one or more of comparing a radius of the first circle to the radius of the second circle to determine the deviation; comparing a center of the first PCOR of the patella to the second PCOR of the patella to determine the deviation; comparing the first plane to the second plane to determine the deviation; and comparing a first extension point and a first flexion point from the set of first data points to a second extension point and a second flexion point from the set of second data points to determine the deviation.
  • the set of first data points is captured prior to a surgical replacement of the knee joint and the set of second data points is captured during a trialing stage of the surgical replacement of the knee joint.
  • the corrective action includes one or more of an adjustment to a polyethylene thickness of an implant of the knee joint; performing a tibial rotation; make a positional adjustment to the implant; making an additional cut of a bone; and performing a soft tissue release.
  • outputting the instruction for performing the corrective action includes the system being configured to execute one or more of displaying a graphical user interface (GUI) element on a display to indicate an adjustment to the polyethylene thickness of the implant, a direction of movement of the tibia, a direction of movement of the implant, or a location of the soft tissue release; outputting a control signal to a robot to implement at least a portion of the corrective action; and generating second instructions, including an indication of a location and a size of a cut to the femur, and sending or displaying the second instructions.
  • GUI graphical user interface
  • Non-transitory computer program products i.e., physically embodied computer program products
  • store instructions which, when executed by one or more data processors (i.e., processing circuit) of one or more computing systems, cause at least one data processor to perform operations herein.
  • data processors i.e., processing circuit
  • computer systems are also described, which may include one or more data processors and memory coupled to the one or more data processors.
  • the memory may temporarily or permanently store instructions that cause at least one processor to perform one or more of the operations described herein.
  • methods can be implemented by one or more data processors, which are either within a single computing system or distributed among two or more computing systems.
  • Such computing systems can be connected and can exchange data and/or commands or other instructions or the like via one or more connections, including but not limited to a connection over a network (e.g., the Internet, a wireless wide area network, a local area network, a wide area network, a wired network, or the like), via a direct connection between one or more of the multiple computing systems, etc.
  • a network e.g., the Internet, a wireless wide area network, a local area network, a wide area network, a wired network, or the like
  • a direct connection between one or more of the multiple computing systems etc.
  • the techniques for patella tracking described herein may operate to provide the use of robotic surgical system capabilities to assess patellar tracking intra-operatively in TKA and/or evaluate and compare patella motion with respect to the femur pre- and post-implantation.
  • existing techniques for patella tracking intra-operatively involve the surgeon passively flexing the knee and observing if the patella dislocates, subluxes, or tilts, either with or without trials or final components.
  • Another technique for intraoperative assessment of patellar tracking is performed after reduction of the patella and involves taking the knee through the full flexion arc without closing the medial arthrotomy and without a medial force from the thumb to keep the patella located.
  • these methods rely too heavily on subjective observations and do not provide adequate imaging capabilities for assessing the patella movement path intra-operatively.
  • FIG. 1 illustrates an example computer-assisted surgical system (CASS) in accordance with one or more features of the present disclosure.
  • CASS computer-assisted surgical system
  • FIG. 2 is a block diagram of an example system in accordance with one or more features of the present disclosure.
  • FIG. 3 is a logic diagram in accordance with one or more features of the present disclosure.
  • FIG. 4 illustrates a data capturing environment in accordance with one or more features of the present disclosure.
  • FIG. 5A illustrates an example graphical user interface (GUI) display in accordance with one or more features of the present disclosure.
  • GUI graphical user interface
  • FIG. 5B illustrates another GUI display in accordance with one or more features of the present disclosure.
  • FIG. 6 illustrates patella tracking images in accordance with one or more features of the present disclosure.
  • FIG. 7A is a femur surface model in accordance with one or more features of the present disclosure.
  • FIG. 7B is a femur surface model in accordance with one or more features of the present disclosure.
  • FIG. 8A is a femur surface model in accordance with one or more features of the present disclosure.
  • FIG. 8B is a femur surface model in accordance with one or more features of the present disclosure.
  • FIG. 9 is a femur surface model in accordance with one or more features of the present disclosure.
  • FIG. 10 is a logic diagram in accordance with one or more features of the present disclosure.
  • FIG. 11 is a flow chart depicting various operations of a method in accordance with one or more features of the present disclosure.
  • FIG. 12 illustrates a computer-readable storage medium in accordance with one or more features of the present disclosure.
  • FIG. 13 is a block diagram of an example computing device in accordance with one or more features of the present disclosure.
  • the knee joint primarily allows for flexion and extension movements, functioning much like a hinge.
  • the knee bends, decreasing the angle between the femur (thigh bone) and the tibia (shin bone). This movement involves the femoral condyles rolling and gliding over the tibial surface.
  • the knee straightens, increasing the angle between the femur and tibia. The tibia glides anteriorly on the femur during this process.
  • the patella plays a crucial role in knee movement by gliding along the femur within the patellofemoral joint. As the knee flexes (bends), the patella moves inferiorly (downward) into the intercondylar groove of the femur. This movement helps to stabilize the knee and allows for smooth motion. When the knee extends (straightens), the patella glides superiorly (upward) along the femur. This gliding action is essential for activities such as walking, squatting, and climbing stairs. The patella also helps to increase the leverage of the quadriceps muscle, enhancing the knee’s ability to extend the leg.
  • Total knee arthroplasty also known as total knee replacement, is a surgical procedure designed to relieve pain and restore function in a knee affected by arthritis or other joint conditions.
  • TKA total knee arthroplasty
  • the damaged surfaces of the knee joint including the femoral condyles and tibial plateau, are replaced with smooth metal and high-grade polyethylene components. This helps to create a new, smooth joint surface.
  • the surgery typically involves making an incision over the knee, removing the damaged cartilage and bone, and then positioning the prosthetic components.
  • the patella may also be resurfaced or replaced.
  • the procedure can be performed using various surgical techniques, including minimally invasive approaches and computer-assisted navigation systems to enhance precision.
  • patella maltracking where the patella moves abnormally within the femoral groove can lead to issues tracking the patella intra-operatively.
  • intraoperative assessment is presently performed by the surgeon visually inspecting and evaluating the patellar tracking during surgery, which is often subjective and relies heavily on the surgeon's experience.
  • the methods and systems disclosed herein provide technical solutions to these technical problems.
  • the disclosed method solves the above problems by using a robotic system to collect objective positional data of the patella intraoperatively as the patella moves from extended to 90° flexion.
  • the positional data collection is performed using a sensor (e.g., a tracked probe) that is used to define the position of the patella.
  • the patella is reduced into the trochlea and a single stitch is placed into the capsule. Doing so allows the contribution of the resting tension in the medial portion of the quadriceps mechanism to be considered.
  • diathermy or a similar marking method is used to etch a mark on the patella that will serve as the ‘constant’ point on the patella during movement.
  • the knee with the patella in the reduced position and with a single stitch in the capsule is taken through a range of 0° to 90° flexion. The knee flexion is performed and continuous or periodic measurements of the position of the patella are captured during this movement.
  • a map of the pathway of the patella is recorded and visually represented on a GUI of a computing device and can be viewed in the coronal plane to obtain a representation of the patella pathway, so called ‘tracking’ and in the sagittal plane to view the patella offset.
  • the stitch can then be removed, and the surgeon continues by registering the tibia, completing the bony cuts, and trialing implants according to their preferences.
  • the patella location data points are then recollected during flexion using the same steps as described above.
  • a patella center of rotation (PCOR) and the patella flexion axis relative to the femur trochlea is determined.
  • the radius of the circle, the center of the PCOR, shift in planes and location of extension and flexion points of the trajectory can be visually presented and also analyzed by the system.
  • the system can determine one or more corrective actions to take to minimize the deviation of the patella movement.
  • One or more instructions can be generated for performing the corrective action and the instructions can be output for review by the surgeon.
  • the instructions can include control instructions to a robot to assist in performing at least a part of the corrective action with the surgeon.
  • Useful machines for performing operations of various examples include digital computers as selectively activated or configured by a computer program stored within that is written in accordance with the teachings herein, and/or include apparatus specially constructed for the required purpose or a digital computer.
  • Various examples also relate to apparatus or systems for performing these operations. These apparatuses may be specially constructed for the required purpose. The required structure for a variety of these machines will be apparent from the description given.
  • FIG. 1 illustrates an example computer-assisted surgical system (CASS) 100, according to some examples of the current subject matter.
  • the CASS may use computers, robotics, and/or imaging technology to aid surgeons in performing orthopedic surgery procedures such as total knee arthroplasty (TKA) or total hip arthroplasty (THA).
  • TKA total knee arthroplasty
  • THA total hip arthroplasty
  • surgical navigation systems may aid surgeons in locating patient anatomical structures, guiding surgical instruments, implanting medical devices with a high degree of accuracy, and/or any other procedures.
  • Surgical navigation systems such as the CASS 100 may employ various forms of computing technology to perform a wide variety of standard and minimally invasive surgical procedures and techniques.
  • the CASS 100 may include one or more of the following: an effector platform 105, a robotic arm 105a, an end effector 105b, a limb positioner 105c, a cutting guide or jig 105d, a tracking system 115, a display 125, a surgical computer 150, and a navigation system 120.
  • a surgeon 11 1 (and/or any other medical professional) may perform a procedure using the CASS 100.
  • the surgeon 111 may wear one or more of an augmented reality head mounted displays, such as, for instance, an AR HMD 155.
  • the effector platform 105 may position surgical tools relative to a patient during a medical procedure, e.g., a surgery.
  • the components of the effector platform 105 may vary, depending on implementations and/or uses of CASS 100.
  • the effector platform 105 may include the end effector 105b that may hold surgical tools and/or instruments during their use.
  • the end effector 105b may be a handheld device or instrument used by the surgeon 111 (e.g., a CORI® hand piece or a cutting guide or jig) and/or, alternatively, or in addition, the end effector 105b may include a device or instrument held or positioned by the robotic arm 105a. While one robotic arm 105a is illustrated in FIG.
  • the robotic arm 105a may be mounted directly to the table, be located next to the table on a floor platform (not shown), mounted on a floor-to-ceiling pole, and/or mounted on a wall or ceiling of an operating room, and/or coupled and/or positioned in any other way.
  • the floor platform may be fixed and/or moveable.
  • the robotic arm 105a may be mounted on a floor-to-ceiling pole located between the patient's legs or feet.
  • the end effector 105b may include a suture holder or a stapler to assist in closing wounds.
  • the surgical computer 150 may operate the robotic arms 105a to work together to suture a wound at closure. Alternatively, or in addition, the surgical computer 150 may operate one or more robotic arm 105a to staple the wound at closure.
  • the effector platform 105 may include the limb positioner 105c for positioning the patient's limbs during surgery.
  • the limb positioner 105c may be operated manually by the surgeon 111 and/or alternatively, or in addition, change limb positions based on instructions received from the surgical computer 150. While one limb positioner 105c is illustrated in FIG. 1, as may be understood, the CASS 100 may include multiple limb positioners 105c and/or devices. For instance, there may be one limb positioner 105c on each side of the operating table and/or two devices on one side of the table.
  • the limb positioner 105c may be mounted directly to the table, be located next to the table on a floor platform (not shown in FIG.
  • the limb positioner 105c may be used in non-conventional ways, such as, for instance, a retractor and/or specific bone holder.
  • the limb positioner 105c may, for instance, include an ankle boot, a soft tissue clamp, a bone clamp, and/or a soft-tissue retractor spoon, such as a hooked, curved, or angled blade, and/or any other component.
  • the limb positioner 105c may include a suture holder to assist in closing wounds.
  • the effector platform 105 may include tools, such as a screwdriver, light and/or laser, to indicate an axis or plane, bubble level, pin driver, pin puller, plane checker, pointer, finger, or some combination thereof.
  • tools such as a screwdriver, light and/or laser, to indicate an axis or plane, bubble level, pin driver, pin puller, plane checker, pointer, finger, or some combination thereof.
  • the CASS 100 may also include a resection equipment (not shown in FIG. 1 ) to perform bone and/or tissue resection using, for example, mechanical, ultrasonic, and/or laser techniques.
  • a resection equipment include drilling devices, burring devices, oscillatory sawing devices, vibratory impaction devices, reamers, ultrasonic bone cutting devices, radio frequency ablation devices, reciprocating devices (such as a rasp or broach), and/or laser ablation systems.
  • the resection equipment is held and operated by the surgeon during surgery.
  • the effector platform 105 may be used to hold the resection equipment during use.
  • the effector platform 105 may also include the cutting guide or jig 105D that may be used to guide saws and/or drills used to resect tissue during surgery.
  • Such cutting guide or jig 105d may be formed integrally as part of the effector platform 105 and/or robotic arm 105a, and/or cutting guides may be separate structures that may be matingly and/or removably attached to the effector platform 105 and/or robotic arm 105a.
  • the effector platform 105 and/or robotic arm 105a may be controlled by the CASS 100 to position a cutting guide or jig 105D adjacent to the patient's anatomy in accordance with a pre-operatively or intraoperatively developed surgical plan such that the cutting guide or jig 105d may produce a precise bone cut in accordance with the surgical plan.
  • the tracking system 115 may use one or more sensors to collect real-time position data that locates the patient's anatomy and surgical instruments. For example, for TKA procedures, the tracking system 115 may provide a location and orientation of the end effector 105b during the procedure. In addition to positional data, data from the tracking system 115 may also be used to infer velocity/acceleration of anatomy/instrumentation, which may be used for tool control. In some examples, the tracking system 115 may use a tracker array attached to the end effector 105b to determine the location and orientation of the end effector 105b.
  • the position of the end effector 105b may be inferred based on the position and orientation of the tracking system 115 and a known relationship in three-dimensional space between the tracking system 115 and the end effector 105b.
  • Various types of tracking systems may be used in various examples of the current subject matter including, but not limited to, infrared (IR) tracking systems, electromagnetic (EM) tracking systems, video or image based tracking systems, ultrasound registration and tracking systems, and/or any other types of tracking systems.
  • IR infrared
  • EM electromagnetic
  • video or image based tracking systems video or image based tracking systems
  • ultrasound registration and tracking systems and/or any other types of tracking systems.
  • the surgical computer 150 may detect objects and/or prevent collision. For instance, the surgical computer 150 may prevent the robotic arm 105a and/or the end effector 105b from colliding with soft tissue.
  • Any suitable tracking system may be used for tracking surgical objects and patient anatomy in the surgical theatre.
  • a combination of IR and visible light cameras may be used in an array.
  • Various illumination sources such as, an IR LED light source, may illuminate the scene allowing three-dimensional imaging to occur. In some examples, this may include stereoscopic, tri-scopic, quad-scopic, etc. imaging.
  • the camera array which in some examples, may be affixed to a cart, additional cameras may be placed throughout the surgical theatre.
  • handheld tools and/or headsets worn by operators/surgeons may include imaging capability that communicates images back to a central processor to correlate those images with images captured by the camera array. This may give a more robust image of the environment for modeling using multiple perspectives.
  • imaging devices may be of suitable resolution and/or have a suitable perspective on the scene to pick up information stored in quick response (QR) codes and/or barcodes. This may be helpful in identifying specific objects not manually registered with the system.
  • the camera may be mounted on the robotic arm 105a.
  • specific objects may be manually registered by a surgeon with the system preoperatively and/or intraoperatively. For instance, by interacting with a user interface, a surgeon 111 may identify the starting location for a tool or a bone structure. By tracking fiducial marks associated with that tool and/or bone structure, and/or by using other conventional image tracking modalities, a processor may track that tool and/or bone as it moves through the environment in a three-dimensional model.
  • certain markers such as, fiducial marks that identify individuals, important tools, and/or bones in the theater may include passive and/or active identifiers that may be picked up by a camera and/or camera array associated with the tracking system.
  • an IR LED may flash a pattern that conveys a unique identifier to the source of that pattern, providing a dynamic identification mark.
  • one or two dimensional optical codes may be affixed to objects in the theater to provide passive identification that may occur based on image analysis. If these codes may be placed asymmetrically on an object, they also may be used to determine an orientation of an object by comparing the location of the identifier with the extents of an object in an image.
  • a QR code may be placed in a corner of a tool tray, allowing the orientation and identity of that tray to be tracked.
  • Other tracking modalities are explained throughout.
  • augmented reality headsets may be worn by surgeons and other staff to provide additional camera angles and tracking capabilities.
  • certain features of objects may be tracked by registering physical properties of the object and associating them with objects that may be tracked, such as, fiducial marks fixed to a tool and/or bone.
  • objects such as, fiducial marks fixed to a tool and/or bone.
  • a surgeon may perform a manual registration process whereby a tracked tool and a tracked bone may be manipulated relative to one another.
  • a three-dimensional surface may be mapped for that bone that is associated with a position and orientation relative to the frame of reference of that fiducial mark.
  • a model of that surface may be tracked with an environment through extrapolation.
  • the registration process that registers the CASS 100 to the relevant anatomy of the patient may also involve use of anatomical landmarks, such as, landmarks on a bone and/or cartilage.
  • the CASS 100 may include a 3D model of the relevant bone and/or joint and the surgeon 111 may intraoperatively collect data regarding the location of bony landmarks on the patient's actual bone using a probe that is connected to the CASS 100.
  • Bony landmarks may include, for example, the medial malleolus and lateral malleolus, the ends of the proximal femur and distal tibia, and the center of the hip joint.
  • the CASS 100 may compare and register the location data of bony landmarks collected by the surgeon with the probe with the location data of the same landmarks in the 3D model. Alternatively, or in addition, the CASS 100 may construct a 3D model of the bone and/or joint without pre-operative image data by using location data of bony landmarks and the bone surface that are collected by the surgeon using a CASS 100 probe and/or other means.
  • the registration process may also include determining various axes of a joint. For example, for a TKA the surgeon 111 may use the CASS 100 to determine the anatomical and mechanical axes of the femur and tibia. The surgeon and the CASS 100 may identify the center of the hip joint by moving the patient's leg in a spiral direction (i.e., circumduction) so the CASS 100 may determine where the center of the hip joint is located.
  • a navigation system 120 may provide the surgeon with intraoperative, real-time visualization for the patient's bone, cartilage, muscle, nervous, and/or vascular tissues surrounding the surgical area.
  • systems that may be employed for tissue navigation include fluorescent imaging systems and ultrasound systems.
  • the display 125 may provide graphical user interfaces (GUIs) that display images collected by the navigation system 120 as well other information relevant to the surgery.
  • GUIs graphical user interfaces
  • the display 125 may overlay image information collected from various modalities (e.g., CT, MRI, X-ray, fluorescent, ultrasound, etc.) collected pre-operatively or intra-operatively to give the surgeon various views of the patient's anatomy as well as real-time conditions.
  • the display 125 may include, for example, one or more computer monitors.
  • one or more members of the surgical staff may wear an Augmented Reality (AR) Head Mounted Device (HMD).
  • AR Augmented Reality
  • the surgeon 111 may wear AR HMD 155 that may, for example, overlay pre-operative image data on the patient or provide surgical planning suggestions.
  • AR HMD 155 may, for example, overlay pre-operative image data on the patient or provide surgical planning suggestions.
  • the surgical computer 150 may provide control instructions to various components of the CASS 100, collects data from those components, and provides general processing for various data needed during surgery.
  • the surgical computer 150 may be a general- purpose computer.
  • the surgical computer 150 may be a parallel computing platform that uses multiple central processing units (CPUs) or graphics processing units (GPU) to perform processing.
  • the surgical computer 150 may be connected to a remote server over one or more computer networks (e.g., the Internet).
  • the remote server may be used, for example, for storage of data or execution of computationally intensive processing tasks.
  • the computers may connect to the surgical computer 150 using a mix of technologies.
  • the end effector 105b may connect to the surgical computer 150 over a wired (i.e., serial) connection.
  • the tracking system 115, navigation system 120, and/or display 125 may similarly be connected to the surgical computer 150 using wired connections.
  • the tracking system 115, navigation system 120, and/or display 125 may connect to the surgical computer 150 using wireless technologies such as, without limitation, Wi-Fi, Bluetooth, Near Field Communication (NFC), or ZigBee.
  • the CASS 100 may include the robotic arm 105a that may serve as an interface to stabilize and/or hold a variety of instruments used during the surgical procedure.
  • these instruments may include, without limitation, retractors, a sagittal or reciprocating saw, the reamer handle, the cup impactor, the broach handle, and the stem inserter.
  • the robotic arm 105a may have multiple degrees of freedom (like a Spider device), and/or have the ability to be locked in place (e.g., by a press of a button, voice activation, a surgeon removing a hand from the robotic arm, or other method).
  • movement of the robotic arm 105a may be effectuated by use of a control panel built into the robotic arm system.
  • a display screen may include one or more input sources, such as physical buttons or a user interface having one or more icons, that direct movement of the robotic arm 105a.
  • the surgeon or other healthcare professional may engage with the one or more input sources to position the robotic arm 105a when performing a surgical procedure.
  • a tool and/or an end effector 105b attached or integrated into the robotic arm 105a may include, without limitation, a burring device, a scalpel, a cutting device, a retractor, a joint tensioning device, or the like.
  • the end effector 105b may be positioned at the end of the robotic arm 105a such that any motor control operations may be performed within the robotic arm system.
  • the tool may be secured at a distal end of the robotic arm 105a, but motor control operation may reside within the tool itself.
  • the robotic arm 105a may be motorized internally to both stabilize the robotic arm, thereby preventing it from falling and hitting the patient, surgical table, surgical staff, etc., and to allow the surgeon to move the robotic arm without having to fully support its weight. While the surgeon is moving the robotic arm 105a, the robotic arm may provide some resistance to prevent the robotic arm from moving too fast or having too many degrees of freedom active at once. The position and the lock status of the robotic arm 105a may be tracked, for example, by a controller or the surgical computer 150.
  • the robotic arm 105a may be moved by hand (e.g., by the surgeon) or with internal motors into its ideal position and orientation for the task being performed.
  • the robotic arm 105a may be enabled to operate in a “free” mode that allows the surgeon to position the arm into a desired position without being restricted. While in the free mode, the position and orientation of the robotic arm 105a may still be tracked as described above.
  • certain degrees of freedom may be selectively released upon input from user (e.g., surgeon) during specified portions of the surgical plan tracked by the surgical computer 150.
  • the robotic arm 105a and/or the end effector 105b may include a trigger or other means to control the power of a saw or drill. Engagement of the trigger or other means by the surgeon may cause the robotic arm 105a and/or end effector 105b to transition from a motorized alignment mode to a mode where the saw or drill is engaged and powered on.
  • the CASS 100 may include a foot pedal (not shown) that causes the system to perform certain functions when activated.
  • the surgeon may activate the foot pedal to instruct the CASS 100 to place the robotic arm 105a and/or end effector 105b in an automatic mode that brings the robotic arm and/or end effector into the proper position with respect to the patient's anatomy in order to perform the necessary resections.
  • the CASS 100 may also place the robotic arm 105a and/or end effector 105b in a collaborative mode that allows the surgeon to manually manipulate and position the robotic arm and/or end effector into a particular location.
  • the collaborative mode may be configured to allow the surgeon to move the robotic arm 105a and/or end effector 105b medially and/or laterally, while restricting movement in other directions.
  • the robotic arm 105a and/or end effector 105b may include a cutting device (saw, drill, and burr) and/or the cutting guide or jig 105d that will guide a cutting device.
  • movement of the robotic arm 105a and/or robotically controlled end effector 105b may be controlled entirely by the CASS 100 without any, or with only minimal, assistance or input from a surgeon or other medical professional.
  • the movement of the robotic arm 105a and/or robotically controlled end effector 105b may be controlled remotely by a surgeon or other medical professional using a control mechanism separate from the robotic arm or robotically controlled end effector device, for example using a joystick or interactive monitor or display control device.
  • the robotic arm 105a may be used for holding the retractor. For example, the robotic arm 105a may be moved into the desired position by the surgeon. At that point, the robotic arm 105a may lock into place. In some examples, the robotic arm 105a is provided with data regarding the patient's position, such that if the patient moves, the robotic arm can adjust the retractor position accordingly. In some examples, multiple robotic arms may be used, thereby allowing multiple retractors to be held or for more than one activity to be performed simultaneously (e.g., retractor holding & reaming). [0088] The robotic arm 105a may also be used to help stabilize the surgeon's hand while making a femoral neck cut.
  • control of the robotic arm 105a may impose certain restrictions to prevent soft tissue damage from occurring.
  • the surgical computer 150 may track the position of the robotic arm 105a as it operates. If the tracked location approaches an area where tissue damage is predicted, a command may be sent to the robotic arm 105a causing it to stop.
  • the surgical computer 150 may ensure that the robotic arm is not provided with any instructions that cause it to enter areas where soft tissue damage is likely to occur.
  • the surgical computer 150 may impose certain restrictions on the surgeon to prevent the surgeon from reaming too far into the medial wall of the acetabulum or reaming at an incorrect angle or orientation.
  • the robotic arm 105a may be used to hold a cup impactor at a desired angle or orientation during cup impaction. When the final position has been achieved, the robotic arm 105a may prevent any further seating to prevent damage to the pelvis.
  • the surgeon may use the robotic arm 105a to position the broach handle at the desired position and allow the surgeon to impact the broach into the femoral canal at the desired orientation.
  • the robotic arm 105a may restrict the handle to prevent further advancement of the broach.
  • the robotic arm 105a may also be used for resurfacing applications.
  • the robotic arm 105a may stabilize the surgeon while using traditional instrumentation and provide certain restrictions or limitations to allow for proper placement of implant components (e.g., guide wire placement, chamfer cutter, sleeve cutter, plan cutter, etc.).
  • implant components e.g., guide wire placement, chamfer cutter, sleeve cutter, plan cutter, etc.
  • the robotic arm 105a may stabilize the surgeon's handpiece and may impose restrictions on the handpiece to prevent the surgeon from removing unintended bone in contravention of the surgical plan.
  • the robotic arm 105a may be a passive arm. Alternatively, or in addition, the robotic arm 105a may be an intelligent holding arm. As can be understood, any other types of robotic arms may be used.
  • FIG. 2 is a block diagram of a system 200 for patella tracking according to some examples of the present disclosure.
  • the system 200 includes any suitable robotic or computing system now know or later discovered capable of performing operations described herein.
  • the system 200 may be a robotic system, computing system, or a mechanical system controlled by a computing device or controller.
  • the system 200 is a single integrated robotic system or multiple components spaced apart (e.g., around a room, in the cloud, on separate floors, etc.) from one another. In the example where the multiple components are spaced apart, the components communicate with each other over a wired or wireless network to work in tandem.
  • the system 200 is a robotic surgical system or modeling surgical system.
  • a robotic surgical system may include the CORI® surgical system from Smith & Nephew, Inc. of Cordova, Tennessee, United States.
  • a robotic surgical system such as CORI®, may be or may include an imageless robotic system providing a versatile platform that empowers surgeons to identify and collect distinctive landmarks, as determined by the operator. When combined with rapid motion capture systems, this technology offers an avenue for measuring the movement of specific landmarks during dynamic motions, such as tracking the patella through its arc of flexion.
  • the system 200 includes a computing device 202 which can include any suitable computing device now known or later discovered.
  • the computing device 202 can be a computer, personal computer (PC), server, cloud server, tablet computer, tablet, iPad® developed by Apple, Inc., microcontroller, controller, central processing unit (CPU), graphics processing unit (GPU), robotic controller, imaging computer system, surgical computer, or any other suitable computing device.
  • the computing device 202 can include the surgical computer 150 from FIG. 1.
  • the system 200 further comprises a sensor 204 (e.g., one or more sensors) and a display 206.
  • the sensor 204 includes a probe, a position sensor, a motion sensor, a motion capture sensor or device, or any other suitable sensor now known or later discovered.
  • the sensor 204 can include tracking device 115 from FIG. 1.
  • the display 206 comprises a monitor, a display, a screen, a user interface, a computer screen, a laptop screen, a mobile device screen, or any other suitable display now known or later discovered.
  • the display 206 includes the display 125 from FIG. 1.
  • the computing device 202 includes a processing circuit 208, a memory 210, a surface model 212 of the femur of a patient undergoing or preparing to undergo surgery to replace a knee joint of the femur, and a communication interface 214.
  • the processing circuit 208 may comprise a processor, microprocessor, central processing unit (CPU), graphics processing unit (GPU), application specific integrated circuit (ASIC), single core processor, multi-core processor, or any other suitable processing circuit, now know or later discovered, that is capable of performing operations described herein.
  • the processing circuit 208 is in communication with the sensor 204 and capable of sending instructions to the sensor 204 (e.g., control instructions to capture data points) and to receive data points captured by the sensor 204.
  • the system 200 includes both a sensor 204 and the tracking device 115 and the tracking device is in communication with the processing circuit 208 as well.
  • the sensor 204 is a probe and the tracking device 115 may track the position of the sensor 204 and communicate position data points of the sensor 204 in three-dimensional space to the processing circuit 208. This may allow the computing device 202 to generate a three-dimensional surface model of the femur and knee joint anatomy of the patient undergoing surgery.
  • the memory 210 comprises a non-transitory memory device, hard drive, solid state drive, flash memory, cache, random access memory (RAM), read only memory (ROM), non-volatile RAM (NVRAM), any combination of these, or any other suitable memory device capable of storing executable instructions for execution by the processing circuit 208.
  • the memory 210 has executable instructions 216 stored thereon, which when accessed and executed by the processing circuit 208 configure the processing circuit 208 to perform various operations described herein.
  • the communication interface 214 of the computing device 202 is used by the computing device 202 to communicate with devices such as the sensor 204, display 206, any storage devices, the tracking device 115, or network devices that the computing device 202 may need to communicate with as part of executing operations described herein.
  • the communication interface 214 may include a receiver, transmitter, transceiver, a wired or wireless data communication interface, an Ethernet interface, a Wi-Fi network interface card (NIC), a wireless radio, antenna, a display port, video port, HDMI port, sensor reception port, USB port, or any other suitable interface for receiving and transmitting data to another device, whether now know or later discovered.
  • the surface model 212 may be stored in the memory 210 or it can be stored on another storage device to which the computing device 202 has access.
  • the memory 210 includes various data and applications stored thereon for execution of or access by the processing circuit 208.
  • the memory 210 may include executable instructions 216, a data collection application 218, a pathway mapping application 220, a motion components application 222, a comparison application 224, and a corrective action application 226 stored thereon for execution by the processing circuit 208.
  • each of these applications or instructions may be embodied in one file or multiple files stored in the memory 210.
  • applications are referred to as applications, this should not be construed as limiting this disclosure. Namely, the functions described by these applications may be performed by a single application or multiple applications.
  • the executable instructions 216 and the various applications described herein include executable instructions, which when executed by the processing circuit 208, cause the system 200 to perform various operations described herein.
  • execution of the executable instructions 216 configures the processing circuit 208 of the system 200 to access a surface model 212 of a femur.
  • the surface model 212 is generated by the processing circuit 208.
  • the processing circuit 208 is configured to communicate with the tracking system 115 and the sensor 204 to collect mapping data that depicts a surface of the femur and the processing circuit 208 is configured to generate the surface model 212 of the femur using the mapping data.
  • the sensor 204 may be a probe and the probe can probe the anatomy of the femur and other parts of the knee joint to determine features of the femur and knee joint, and these features are included as the mapping data.
  • the tracking system 115 may collect readings from the sensor 204 as it probes the knee joint and anatomy of the patient.
  • the mapping data and features of the femur and knee joint can be used to generate the surface model 212.
  • execution of the data collection application 218 configures the processing circuit 208 to collect, using the sensor 204, a set of first data points defining a first movement of a patella during a first flexion of a knee joint of the femur.
  • Collecting the set of first data points may be performed intra-operatively and is performed before a knee replacement has occurred. That is, collecting the set of first data points defining the first movement of the patella is performed on the native anatomy of the femur and knee joint prior to a surgical replacement of the knee joint (e.g., replaced with a knee implant system or device).
  • the processing circuit 208 is configured to collect, using the sensor 204, a set of second data points defining a second movement of the patella during a second flexion of the knee joint. For example, after part of the knee joint has been replaced or during a trialing stage of the surgical replacement of the knee joint, the trialing stage for testing whether the implant is correctly placed to ensure patient comfort and knee implant success, the set of second data points are captured.
  • collecting the set of first data points and the set of second data points using the sensor 204 includes the system 200, or the processing circuit 208, being configured to identify, from data collected by the sensor 204, at least one point on the patella (e.g., a single point, or a plurality of points, including three or more points on the patella such as, for example, orientated like a tripod, so that the system not only captures the movement of the patella through the range of motion, but also its orientation and whether it tilts more medially or laterally during that motion). These are a plurality of points in three-dimensional space. The at least one point may be determined using the sensor 204 or the sensor 204 along with the tracking system 115.
  • the tracking system 115 may help determine where in three-dimensional space the at least one point on the patella is located by detecting where the sensor 204 is located in the operation area. From there, the processing circuit 208 or system 200 is configured to collect, using the sensor 204, movement data of the at least one point on the patella, wherein the set of first data points includes movement data of the at least one point during the first flexion and the set of second data points includes movement data of the at least one point during the second flexion. As such, before the surgery is performed the movement data of the at least one point of the patella is gathered and this is the set of first data points and during the trialing stage with the knee implant in place, the movement data of the at least one point of the patella is gathered again and this is the set of second data points.
  • the data points may be collected during a movement of the knee joint from extended to a flexion of 90 degrees.
  • the sensor 204 is attached to the patella and collecting the set of first data points and the set of second data points using the sensor 204 includes the system 200 being configured to use a motion capture device (e.g., tracking system 115) to detect motion of the sensor 204, and thereby the patella, as the sensor 204 moves with the patella during the first flexion and the second flexion of the knee joint.
  • a motion capture device e.g., tracking system 115
  • a patella bone 3D model may be created and, by registering the patella bone and tracking the patella, more information, such as rotational motion of the patella, can be collected and used to provide additional representation of patella tracking.
  • three or more points of the patella can be tracked using methods according to some methods to better understand the 3D kinematics of the patella.
  • the processing circuit 208 executes the pathway mapping application 220 configuring the processing circuit 208 to map a first pathway and a second pathway of the patella on the surface model 212 of the femur.
  • the first pathway is defined by the set of first data points and the second pathway is defined by the set of second data points.
  • a visualization of the mapping the first and second pathways is provided at FIG. 5A, FIG. 5B, and FIG. 6 below.
  • the processing circuit 208 executes the motion components application 222 configuring the processing circuit 208 to determine, based on the first pathway and the second pathway of the patella, first patella motion components and second patella motion components of the patella.
  • the first patella motion components and the second patella motion components help define or characterize the motion of the patella of the knee joint before the surgical procedure (e.g., first patella motion components) to replace the knee joint and during the trialing stage (e g., the second patella motion components) of the knee replacement operation, respectively.
  • FIG. 3 below provides a more detailed description of determining the first patella motion components and the second patella motion components.
  • the processing circuit 208 executes the comparison application 224 configuring the processing circuit 208 to compare the first patella motion components to the second patella motion components to determine a deviation in a motion of the patella from the native anatomy of the knee joint to the knee joint with the knee implant surgically in place.
  • FIG. 3, FIG. 8A, and FIG. 8B provide greater detail on comparing the first patella motion components to the second patella motion components to determine the deviation.
  • the processing circuit 208 executes the corrective action application 226 configuring the processing circuit 208 to determine, based on the deviation determined above, and the surface model 212 of the femur, a corrective action to be performed that will minimize the deviation in the motion of the patella.
  • the corrective action includes one or more of making an adjustment to a polyethylene thickness of an implant of the knee joint; performing a tibial rotation; making a positional adjustment to the implant; making an additional cut of a bone; and performing a soft tissue release.
  • a machine learning (ML) model may be used to analyze the deviation, and based on training data provided to the ML model, the ML model may predict and output a proposed corrective action.
  • the ML model may analyze the deviation and the surface model 212, including an updated surface model with the implant in place, and determine that an additional bone cut is most likely to minimize the deviation.
  • the ML model may output details regarding the additional bone cut and making an additional cut of the bone may be selected as the corrective action.
  • the processing circuit 208 is further configured to use the communication interface 214 to output an instruction for performing the corrective action.
  • the processing circuit 208 may be configured to execute one or more of displaying a graphical user interface (GUI) element on the display 206, or sending a GUI element to the display 206 for displaying thereon, to indicate an adjustment to the polyethylene thickness of the implant, a direction of movement of the tibia, a direction of movement of the implant, or a location of the soft tissue release.
  • the processing circuit 208 is configured to output a control signal to a robot, such as CASS 100, to implement at least a portion of the corrective action.
  • control signal may be sent to the CASS 100 to instruct the robotic arm 105a, or the limb positioner 105c to implement at least a portion of the corrective action (e.g., moving the patient's leg to assist in performing a cut, or any other suitable action by the robot to aide in implementing the corrective action).
  • the processing circuit 208 is configured to generate second instructions, including an indication of a location and a size of a cut to the femur, and sending or displaying the second instructions on the display 206. The location and size of the cut to the femur may be determined or predicted using the ML model described above.
  • FIG. 3 is a logic diagram 300 depicting various operations the processing circuit 208 is configured to execute in order to collect the sets of first data points and second data points and determine therefrom the first patella motion components and second patella motion components.
  • the first patella motion components and second patella motion components help define or characterize the motion of the patella of the knee joint before and after the surgical procedure.
  • the processing circuit 208 is configured to collect, using the sensor 204, a set of first data points defining a first movement of a patella during a first flexion of a knee joint of the femur.
  • the processing circuit 208 is configured to collect, using the sensor 204, a set of second data points defining a second movement of the patella during a second flexion of the knee joint.
  • the processing circuit 208 is configured to map a first pathway and a second pathway of the patella on the surface model of the femur, the first pathway being defined by the set of first data points and the second pathway being defined by the set of second data points.
  • the processing circuit 208 is configured to make, based on the first pathway and the second pathway of the patella, patella motion components determinations 308. These components help define a center of rotation of the patella and a flexion axis thereof. These components aide in comparing the pathway of the patella before and after the knee implant and therefore help determine the deviation described above.
  • the processing circuit 208 is configured to determine first patella motion components of the native anatomy before the knee implant is in place.
  • the processing circuit 208 is configured to fit a first plane 310 to the set of first data points, wherein the first plane is defined by a centroid of the set of first data points and a normal vector that is perpendicular to a direction of the set of first data points.
  • the first plane is determined using a three-dimensional (3D) least squares plane fitting algorithm to determine and fit the first plane to the set of first data points.
  • 3D least squares plane fitting algorithm is a method used to find the best-fitting plane through a set of 3D points. This technique minimizes the sum of the squared distances (e g., residuals) between the points and the plane.
  • performing this technique involves several operations performed by the processing circuit 208.
  • the processing circuit 208 is configured to determine coordinates in 3D space for each of the first data points. These coordinates take the form z,).
  • the processing circuit 208 is configured to set up a system of linear equations for each point (x y z,) in the set of first data points.
  • the processing circuit 208 is configured to substitute the coordinates into the plane equation (e.g., Equation 1) to obtain the system of linear equations.
  • the processing circuit 208 is configured to minimize the residuals. In some examples, this involves the processing circuit 208 using the least squares method to minimize the sum of the squared residuals. This involves solving a system of normal equations derived from the partial derivatives of the residual sum with respect to the plane parameters a, b, c, and d.
  • the processing circuit 208 is configured to solve the normal equations.
  • the normal equations can be solved using matrix operations to find the values of a, b, c, and d that define the best fitting plane.
  • Coefficients a, b, and c define the direction cosines of the normal vector to the plane, and they determine the orientation of the plane in 3D space.
  • the coefficient d is the distance from the origin to the plane, scaled by the magnitude of the normal vector. It essentially shifts the plane along the normal vector. Together, these coefficients define the position and orientation of the plane that best fit the set of first data points.
  • the processing circuit 208 is configured to project the set of first data points onto the first plane and then fit a first circle 312 to the projected set of first data points.
  • the set of first data points are projected to the plane by using the normal vector of the plane. For every point, the intersection of a line drawn from that point in the normal direction of the plane and the plane itself, represents the projection of the point onto the plane.
  • the processing circuit 208 is configured to fit the first circle to the projected set of first data points using a linear least squares method. This method involves finding the circle's parameters (center and radius) that minimize the sum of the squared distances between the set of first data points and the circle.
  • the equation of a circle in 2D is depicted by Equation 2 below. Coordinates (x c , j c ) define the center of the circle and r is the radius.
  • the processing circuit 208 is configured to linearize the circle equation by expanding and rearranging the variables. Equation 3
  • the center of the first circle defines a first patella center of rotation (POOR) of the patella during the first flexion.
  • a first axis passing through the center of the first circle in a direction of the first plane's normal vector defines a first patella flexion axis relative to a femur trochlea of the femur, during the first flexion.
  • FIG. 7B provides a visual representation of an example of the PCOR and the patella flexion axis.
  • the first patella motion components include the first PCOR and the first patella flexion axis.
  • the processing circuit 208 is configured to repeat the operations above for the set of second data points to determine the second patella motion components. Namely, the processing circuit 208 is configured to fit a second plane 314 to the set of second data points as described above. The second plane is defined by a centroid of the set of second data points and a normal vector that is perpendicular to a direction of the set of second data points. Then the processing circuit 208 is configured to project the set of second data points onto the second plane as described above. Next, the processing circuit 208 is configured to fit a second circle 316 to the projected set of second data points as described above.
  • the center of the second circle defines a second PCOR of the patella during the second flexion and a second axis passing through the center of the second circle in a direction of the second plane's normal vector defines a second patella flexion axis relative to the femur trochlea of the femur, during the second flexion.
  • the second patella motion components include the second PCOR and the second patella flexion axis.
  • comparing the first patella motion components to the second patella motion components to determine the deviation includes the processing circuit 208 being configured to execute one or more of comparing a radius of the first circle to the radius of the second circle to determine the deviation; comparing a center of the first PCOR of the patella to the second PCOR of the patella to determine the deviation; comparing the first plane to the second plane to determine the deviation; and comparing a first extension point and a first flexion point from the set of first data points to a second extension point and a second flexion point from the set of second data points to determine the deviation.
  • the deviation can include a combination of factors characterizing the deviation between the two sets of data points.
  • the deviation between the curves (e.g., patella pathways) defined by the set of first data points and set of second data points can be determined by using a distance measuring algorithm to determine an average distance between the curves.
  • a distance measuring algorithm to determine an average distance between the curves.
  • Other methods for determining the deviation may include using a dynamic time warping algorithm, determining a Frechet distance between the curves, determining the Hausdorff distance between the curves, using an Algorithm for finding the Least-Cost Areal Mapping between Paths (ALCAMAP) to measure the deviation by mapping corresponding points on the paths and calculating the area between them, using regression models, or gradient-based optimization techniques.
  • ALCAMAP Least-Cost Areal Mapping between Paths
  • the deviations determined, along with the surface model 212 before and after the implant can be fed into a machine learning model trained for determining corrective actions based on the deviations.
  • the corrective action may include one or more of making an adjustment to a polyethylene thickness of an implant of the knee joint; performing a tibial rotation; making a positional adjustment to the implant; making an additional cut of a bone; and performing a soft tissue release.
  • the processing circuit 208 is configured to display, on a graphical user interface (e.g., on display 206), the surface model of the femur (e.g., the femur, knee joint, patella with knee joint, etc.) with one or more of the first circle, the second circle, the first plane, the second plane, the set of first data points, the set of second data points, the center of the first circle, the center of the second circle, the first patella flexion axis, and the second patella flexion axis projected thereon. Examples of such display include FIG. 6, FIG. 7A, FIG. 7B, FIG. 8A, and FIG. 8B.
  • FIG. 4 illustrates an example data capturing environment 400 according to some examples of the present disclosure.
  • the set of first data points and set of second data points are captured of the patella as it moves from an extended state to a 90° flexion state.
  • FIG. 4 illustrates a knee joint 402 in the extended position and in the 90° flexion state.
  • the sensor 204 which can include a probe attached to the patella or the tracking system 115 tracking at least one point on the patella or tracking the sensor 204 that is attached to the patella.
  • the tracking system 115 tracks the movement of the sensor 204 as the knee joint 402 goes from extension to the 90° flexion state.
  • the capturing of the movement of the patella is ended and the data points captured while the knee flexes is recorded to a file (e.g., text file) in memory 210 of the computing device 202.
  • a file e.g., text file
  • the set of first data points characterize the position of the at least one point on the patella in 3D space (e.g., 3D coordinates).
  • the sensor 204 is configured to capture the movement of the patella as the knee joint 402 is flexed.
  • the set of second data points also characterize the position of the at least one point on the patella in 3D space (e.g., 3D coordinates).
  • the set of second data points are saved to a file as well and stored in memory 210.
  • the set of second data points may be saved to the same file as the set of first data points.
  • the set of first data points and the set of second data points are recorded in a single text file without any divisions that separate the groups.
  • the distances between each set of two consecutive points are calculated. When a significant jump occurs in the distance between two consecutive points, it indicates the transition from pre-implant points to post-implant points. This results in two distinct sets of points: one for pre-implant and one for post-implant.
  • the sensor 204, tracking system 115, and/or computing device 202 are configured to continuously track the motion of the patella throughout the flexion. For example, each data point of the location of the at least one point on the patella can be captured periodically (e.g., every second, millisecond, microsecond, nanosecond, or any suitable time period to provide adequate data for characterizing movement of the patella).
  • FIG. 5A illustrates a GUI display 500 of a lateral view of the native anatomy 502 of the femur (e.g., a surface model) before the surgical implant has been provided to the patient.
  • a GUI display 500 of a lateral view of the native anatomy 502 of the femur e.g., a surface model
  • Such an image can be displayed on the display 206 as described above.
  • Displayed on the image is the first pathway 504 of the patella as the knee joint is flexed as described above.
  • the first pathway 504 is characterized by at least a portion of the set of first data points collected by the sensor 204, tracking system 115, and/or processing circuit 208 before the surgery is performed.
  • FIG. 5B illustrates the GUI display 500 of FIG. 5A, but here, the knee replacement trial anatomy 506 is provided on the GUI display 500. Moreover, the first pathway and second pathway 508 of the patella motion are provided on the GUI display 500.
  • the first pathway and second pathway 508 are characterized by at least a portion of the set of first data points and set of second data points, respectively, that were collected by the sensor 204, tracking system 115, and/or processing circuit 208 before and after the surgery is performed.
  • FIG. 6 provides patella tracking images 600 similar to those depicted above on the GUI display 500 in FIG. 5 A and FIG. 5B.
  • These patella tracking images 600 provide an axial view of distal femur 602 and a lateral view of distal femur 604, both with the knee replacement surgically implanted.
  • the axial view of distal femur 602 and the lateral view of distal femur 604 both include the first (pre-operation) pathway 606 and the second (trial period) pathway 608 displayed thereon, indicating a movement of the patella across the knee joint both before and after the knee replacement surgery.
  • the processing circuit 208 is configured to determine the extent of this deviation and then determine one or more corrective actions to suggest to the surgeon. This may include any of the corrective actions provided above.
  • FIG. 7A is a femur surface model 700 with the first (pre-operation) pathway 606 projected thereon.
  • a plane 702 in order to determine the first patella motion components, a plane 702 must be fitted to the coordinates of the set of first data points.
  • the femur surface model 700 includes the plane 702 with the set of first data points projected thereon.
  • a circle 704 is fitted to the set of first data points on the plane 702. As described above, the radius and the center of the circle is determined.
  • FIG. 7B illustrates the femur surface model 700 with the first pathway 606, plane 702, circle 704 and center of the fitted circle 706 depicted thereon. As described above the center of the fitted circle 706 characterizes the PORC of the patella. A patella flexion axis 708 is also depicted on the femur surface model 700.
  • FIG. 8A illustrates the femur surface model 700 from FIG. 7A and FIG. 7B, however, in this view, both the first pathway and the second pathway are depicted. Moreover, the planes for each set of data points and the first fitted circle 802 and second fitted circle 804 are also provided. Finally, the center of the first circle 806 and the center of the second circle 808 are depicted as well. Those having ordinary skill in the art will note that the radius of the second fitted circle 804 is greater than radius of the first fitted circle 802 highlighting a deviation between the first pathway and second pathway. Furthermore, the center of the second circle 808 is spaced apart from the center of the first circle 806 highlighting the deviation in the pathways as well.
  • the insights can help analyzed by a machine learning model to determine the corrective action described above.
  • first fitted circle 802 can help the surgeon analyze the two pathways and determine a corrective action on their own.
  • second fitted circle 804 center of the first circle 806, and center of the second circle 808 can help the surgeon analyze the two pathways and determine a corrective action on their own.
  • FIG. 8B illustrates another angle of the femur surface model 700 from FIG. 8A and highlights another piece of data. Namely, the first fitted circle 802 and second fitted circle 804 are not aligned with each other. This other perspective indicates a deviation between the two circles beyond just a different radius as indicated by FIG. 8A. These deviations in the patella pathways may be significant enough to cause pain and discomfort to the patient. As such, corrective action may need to be taken to minimize the deviation and better align the first and second pathways.
  • FIG. 9 depicts a femur surface model 900 with a first pathway 902 and second pathway 904 projected thereon.
  • the second pathway 904 appears to have noise in the data capture. This noise is characterized by the sharp (i.e., 90 degree) turn right of the data. Noise of this character may be caused by issues with the sensor, a bump of the knee, or some other reason.
  • the set of second data points includes both the non-noisy data points and noisy datapoints.
  • the logic diagram 1000 in FIG. 10 describes one example method for correcting for this noise.
  • the second pathway 904 includes a noisy dataset, whereby the noise 906 is characterized by the significant deviation of datapoints in the second pathway 904.
  • FIG. 10 is a logic diagram 1000 depicting example operations performed by the processing circuit 208 to minimize or eliminate this noise to fit the plane and circle to the second pathway 904 as described using the techniques above.
  • the sets of data points that characterize the first pathway 902 and the second pathway 904 are collected as described above.
  • the collected data points are then analyzed to detect instances of noise (e.g., noise 906). Instances of noise may be detected based on significant deviations in the data points. For example, the noise 906 in FIG. 9 shows a right degree turn of the data points. This is very unlikely to occur with normal patella movement.
  • DBSCAN density-based spatial clustering of applications with noise
  • an isolation forest algorithm may be used to detect noise in the data sets.
  • An isolation forest builds an ensemble of trees and uses the path length from the root to the leaf to determine anomalies. This method is ideal for detecting anomalies in high-dimensional data, including pathways. It isolates observations by randomly selecting features and split values, making it robust against noise.
  • an autoencoder may be used to detect noise in the data sets.
  • Autoencoders are neural networks that can learn to reconstruct input data. For pathway data, high reconstruction error can indicate noisy points.
  • autoencoder may be trained on the pathway data and may use the reconstruction error to identify and filter out noisy points.
  • a dynamic time warping (DTW) method may be used to detect noise in the data sets.
  • a DTW measures the similarity between two sequences by finding an optimal match that minimizes the distance between them, highlighting noisy segments.
  • DTW is useful for temporal and sequential data, such as pathways, as it can align sequences non-linearly and detect deviations.
  • a Frechet distance may be used to detect noise in the data sets. This method calculates the maximum distance a person and a dog would travel while walking along the two curves, identifying significant deviations. The algorithm is intuitive for pathway data as it measures the "dog-walking" distance between two curves, capturing the overall shape and location differences.
  • the detected noisy data points are removed from the set of first data points or set of second data points.
  • the first plane 702 and/or the second plane 702 are refit to the set of first data points and set of second data points, respectively.
  • the first fitted circle 802 and/or the second fitted circle 804 are re-determined.
  • the plane and circle of the set of data points with noise removed is redetermined. From there, the operations described above proceeds with the noisy data removed.
  • FIG. 1 1 is a flow chart illustrating some example operations performed in a method 1 100 for patella tracking.
  • the method 1100 includes accessing, by a computing device, a surface model of a femur.
  • the method 1100 includes collecting, using a sensor in communication with the computing device, a set of first data points defining a first movement of a patella during a first flexion of a knee joint of the femur.
  • the method 1100 includes collecting, using the sensor, a set of second data points defining a second movement of the patella during a second flexion of the knee joint.
  • the method 1100 includes mapping, by the computing device, a first pathway and a second pathway of the patella on the surface model of the femur, the first pathway being defined by the set of first data points and the second pathway being defined by the set of second data points.
  • the method 1 100 includes determining, by the computing device and based on the first pathway and the second pathway of the patella, first patella motion components and second patella motion components of the patella. As shown at block 1112, the method 1100 includes comparing, by the computing device, the first patella motion components to the second patella motion components to determine a deviation in a motion of the patella. As shown at block 1114, the method 1100 includes determining, by the computing device and based on the deviation and the surface model of the femur, a corrective action to minimize the deviation in the motion of the patella. As shown at block 1116, the method 1100 includes outputting, by the computing device, an instruction for performing the corrective action. [0156] In some examples, the method 1100 includes collecting, using the sensor, mapping data that depicts a surface of the femur; and generating, by the computing device, the surface model of the femur using the mapping data.
  • collecting the set of first data points and the set of second data points using the sensor includes identifying, by the computing device from data collected by the sensor, at least one point on the patella; and collecting, by the computing device using the sensor, movement data of the at least one point on the patella, wherein the set of first data points includes movement data of the at least one point during the first flexion and the set of second data points includes movement data of the at least one point during the second flexion.
  • the senor is attached to the patella; and in some examples of the method 1100, collecting the set of first data points and the set of second data points using the sensor includes the computing device using a motion capture device to detect motion of the sensor, and thereby the patella, as the sensor moves with the patella during the first flexion and the second flexion.
  • determining the first patella motion components comprises fitting, by the computing device, a first plane to the set of first data points, wherein the first plane is defined by a centroid of the set of first data points and a normal vector that is perpendicular to a direction of the set of first data points; projecting, by the computing device, the set of first data points onto the first plane; and fitting, by the computing device, a first circle to the projected set of first data points; wherein a center of the first circle defines a first patella center of rotation (PCOR) of the patella during the first flexion; wherein a first axis passing through the center of the first circle in a direction of the first plane's normal vector defines a first patella flexion axis relative to a femur trochlea of the femur, during the first flexion; and wherein the first patella motion components include the first PCOR and the first patella flexion axis.
  • PCOR patella center of rotation
  • determining the second patella motion components comprises fitting, by the computing device, a second plane to the set of second data points, wherein the second plane is defined by a centroid of the set of second data points and a normal vector that is perpendicular to a direction of the set of second data points; projecting, by the computing device, the set of second data points onto the second plane; and fitting, by the computing device, a second circle to the projected set of second data points; wherein a center of the second circle defines a second PCOR of the patella during the second flexion; wherein a second axis passing through the center of the second circle in a direction of the second plane's normal vector defines a second patella flexion axis relative to the femur trochlea of the femur, during the second flexion; and wherein the second patella motion components include the second PCOR and the second patella flexion axis.
  • the method 1100 further includes displaying, by the computing device on a graphical user interface, the surface model of the femur with one or more of the first circle, the second circle, the first plane, the second plane, the set of first data points, the set of second data points, the center of the first circle, the center of the second circle, the first patella flexion axis, and the second patella flexion axis projected thereon.
  • comparing the first patella motion components to the second patella motion components to determine the deviation comprises one or more of comparing, by the computing device, a radius of the first circle to the radius of the second circle to determine the deviation; comparing, by the computing device, a center of the first PCOR of the patella to the second PCOR of the patella to determine the deviation; comparing, by the computing device, the first plane to the second plane to determine the deviation; and comparing, by the computing device, a first extension point and a first flexion point from the set of first data points to a second extension point and a second flexion point from the set of second data points to determine the deviation.
  • the set of first data points is captured prior to a surgical replacement of the knee joint and the set of second data points is captured during a trialing stage of the surgical replacement of the knee joint.
  • the corrective action includes one or more of adjusting a polyethylene thickness of an implant of the knee joint; performing a tibial rotation; making a positional adjustment to the implant; making an additional cut of a bone; and performing a soft tissue release.
  • outputting the instruction for performing the corrective action includes one or more of displaying a graphical user interface (GUI) element on a display to indicate an adjustment to the polyethylene thickness of the implant, a direction of movement of the tibia, a direction of movement of the implant, or a location of the soft tissue release; outputting a control signal to a robot to implement at least a portion of the corrective action; and generating second instructions, including an indication of a location and a size of a cut to the femur, and sending or displaying the second instructions.
  • GUI graphical user interface
  • Apparatus 1200 comprises any non-transitory computer-readable storage medium 1202 or machine-readable storage medium, such as an optical, magnetic or semiconductor storage medium.
  • apparatus 1200 comprises an article of manufacture or a product.
  • the computer-readable storage medium 1202 stores computer executable instructions with which one or more processing devices or processing circuitry can execute.
  • computer executable instructions 1204 includes instructions to implement operations described with respect to any method, operation, logic flows, timing diagram, or example described herein.
  • Examples of computer-readable storage medium 1202 or machine-readable storage medium include any tangible media capable of storing electronic data, including volatile memory or non-volatile memory, removable or nonremovable memory, erasable or non-erasable memory, writeable or re-writeable memory, and so forth.
  • Examples of computer executable instructions 1204 include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visual code, and the like.
  • Some examples of the present disclosure include non-transitory computer readable storage media, such as computer-readable storage medium 1202, that store computer executable instructions 1204 that, when executed, configure a processing circuit to perform operations described herein.
  • FIG. 13 illustrates an example of an exemplary computer architecture 1300 suitable for implementing various examples as previously described.
  • the computer architecture 1300 can be used to implement the system 200 described in FIG. 2.
  • the computer architecture 1300 may include or be implemented as part of one or more systems or devices discussed herein.
  • the computer architecture 1300 includes components that can implement one or more of the computing apparatus or any other computing device described above.
  • system and “component” are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution, examples of which are provided by the exemplary computer architecture 1300.
  • a component can be, but is not limited to being, a process running on a processor, a processor, a hard disk drive, multiple storage drives (of optical and/or magnetic storage medium), an object, an executable, a thread of execution, a program, and/or a computer.
  • an application running on a server and the server can be a component.
  • One or more components can reside within a process and/or thread of execution, and a component can be localized on one computer and/or distributed between two or more computers. Further, components may be communicatively coupled to each other by various types of communications media to coordinate operations. The coordination may involve the uni-directional or bidirectional exchange of information. For instance, the components may communicate information in the form of signals communicated over the communications media. The information can be implemented as signals allocated to various signal lines. In such allocations, each message is a signal. Further examples, however, may alternatively employ data messages. Such data messages may be sent across various connections. Exemplary connections include parallel interfaces, serial interfaces, and bus interfaces.
  • the computer architecture 1300 includes various common computing elements, such as one or more processors, multi-core processors, co-processors, processing circuit(s), memory units, chipsets, controllers, peripherals, interfaces, oscillators, timing devices, video cards, audio cards, multimedia input/output (I/O) components, power supplies, and so forth.
  • processors multi-core processors
  • co-processors processing circuit(s)
  • memory units chipsets
  • controllers peripherals, interfaces, oscillators, timing devices, video cards, audio cards, multimedia input/output (I/O) components, power supplies, and so forth.
  • I/O multimedia input/output
  • the computer architecture 1300 includes a processor 1312, a system memory 1304 and a system bus 1306.
  • the processor 1312 can be any of various commercially available processors or processor circuits.
  • the system bus 1306 provides an interface for system components including, but not limited to, the system memory 1304 to the processor 1312.
  • the system bus 1306 can be any of several types of bus structure that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures.
  • Interface adapters may connect to the system bus 1306 via slot architecture.
  • Example slot architectures may include without limitation Accelerated Graphics Port (AGP), Card Bus, (Extended) Industry Standard Architecture ((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral Component Interconnect (Extended) (PCI(X)), PCI Express, Personal Computer Memory Card International Association (PCMCIA), and the like.
  • the computer architecture 1300 may include or implement various articles of manufacture.
  • An article of manufacture may include a computer-readable storage medium to store logic.
  • Examples of a computer-readable storage medium may include any tangible media capable of storing electronic data, including volatile memory or non-volatile memory, removable or non-removable memory, erasable or non-erasable memory, writeable or re-writeable memory, and so forth.
  • Examples of logic may include executable computer program instructions implemented using any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visual code, and the like, examples may also be at least partly implemented as instructions contained in or on a non- transitory computer-readable medium, which may be read and executed by one or more processors to enable performance of the operations described herein.
  • suitable type of code such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visual code, and the like
  • examples may also be at least partly implemented as instructions contained in or on a non- transitory computer-readable medium, which may be read and executed by one or more processors to enable performance of the operations described herein.
  • the system memory 1304 may include various types of computer-readable storage media in the form of one or more higher speed memory units, such as read-only memory (ROM), random-access memory (RAM), dynamic RAM (DRAM), Double-Data-Rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory such as ferroelectric polymer memory, ovonic memory, phase change or ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic or optical cards, an array of devices such as Redundant Array of Independent Disks (RAID) drives, solid state memory devices (e.g., USB memory, solid state drives (SSD) and any other type of storage media suitable for storing information.
  • the system memory 1304 can include non-volatile 1308 and/or volatile 1310.
  • the computer 1302 may include various types of computer-readable storage media in the form of one or more lower speed memory units, including an internal (or external) hard disk drive 1330, a magnetic disk drive 1316 to read from or write to a removable magnetic disk 1320, and an optical disk drive 1328 to read from or write to a removable optical disk 1332 (e.g., a CD- ROM or DVD).
  • the hard disk drive 1330, magnetic disk drive 1316 and optical disk drive 1328 can be connected to system bus 1306 the by an HDD interface 1314, and FDD interface 1318 and an optical disk drive interface 1334, respectively.
  • the HDD interface 1314 for external drive implementations can include at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.
  • USB Universal Serial Bus
  • the drives and associated computer-readable media provide volatile and/or nonvolatile storage of data, data structures, computer-executable instructions, and so forth.
  • a number of program modules can be stored in the drives and non-volatile 1308, and volatile 1310, including an operating system 1322, one or more applications 1342, other program modules 1324, and program data 1326.
  • the one or more applications 1342, other program modules 1324, and program data 1326 can include, for example, the various applications and/or components of the systems discussed herein.
  • a user can enter commands and information into the computer 1302 through one or more wire/wireless input devices, for example, a keyboard 1350 and a pointing device, such as a mouse 1352.
  • Other input devices may include microphones, infra-red (IR) remote controls, radiofrequency (RF) remote controls, game pads, stylus pens, card readers, dongles, finger print readers, gloves, graphics tablets, joysticks, keyboards, retina readers, touch screens (e.g., capacitive, resistive, etc.), trackballs, track pads, sensors, styluses, and the like.
  • IR infra-red
  • RF radiofrequency
  • input devices are often connected to the processor 1312 through an input device interface 1336 that is coupled to the system bus 1306 but can be connected by other interfaces such as a parallel port, IEEE 1394 serial port, a game port, a USB port, an IR interface, and so forth.
  • a monitor 1344 or other type of display device is also connected to the system bus 1306 via an interface, such as a video adapter 1346.
  • the monitor 1344 may be internal or external to the computer 1302.
  • a computer typically includes other peripheral output devices, such as speakers, printers, and so forth.
  • the computer 1302 may operate in a networked environment using logical connections via wire and/or wireless communications to one or more remote computers, such as a remote computer(s) 1348.
  • the remote computer(s) 1348 can be a workstation, a server computer, a router, a personal computer, portable computer, microprocessor-based entertainment appliance, a peer device or other common network node, and typically includes many or all the elements described relative to the computer 1302, although, for purposes of brevity, only a memory and/or storage device 1358 is illustrated.
  • the logical connections depicted include wire/wireless connectivity to a local area network 1356 (LAN) and/or larger networks, for example, a wide area network 1354 (WAN).
  • LAN and WAN networking environments are commonplace in offices and companies, and facilitate enterprise-wide computer networks, such as intranets, all of which may connect to a global communications network, for example, the Internet.
  • the computer 1302 When used in a local area network 1356 networking environment, the computer 1302 is connected to the local area network 1356 through a wire and/or wireless communication network interface or network adapter 1338.
  • the network adapter 1338 can facilitate wire and/or wireless communications to the local area network 1356, which may also include a wireless access point disposed thereon for communicating with the wireless functionality of the network adapter 1338.
  • the computer 1302 When used in a wide area network 1354 networking environment, the computer 1302 can include a modem 1340, or is connected to a communications server on the wide area network 1354 or has other means for establishing communications over the wide area network 1354, such as by way of the Internet.
  • the modem 1340 which can be internal or external and a wire and/or wireless device, connects to the system bus 1306 via the input device interface 1336.
  • program modules depicted relative to the computer 1302, or portions thereof can be stored in the remote memory and/or storage device 1358. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers can be used.
  • the computer 1302 is operable to communicate with wire and wireless devices or entities using the IEEE 1202 family of standards, such as wireless devices operatively disposed in wireless communication (e g., IEEE 1202.11 over-the-air modulation techniques).
  • wireless communication e g., IEEE 1202.11 over-the-air modulation techniques.
  • the communication can be a predefined structure as with a conventional network or simply an ad hoc communication between at least two devices.
  • Wi-Fi networks use radio technologies called IEEE 802.11 (a, b, g, n, etc.) to provide secure, reliable, fast wireless connectivity.
  • a Wi-Fi network can be used to connect computers to each other, to the Internet, and to wire networks (which use IEEE 802.3-related media and functions).
  • the various elements of the devices as previously described herein may include various hardware elements, software elements, or a combination of both.
  • hardware elements may include devices, logic devices, components, processors, microprocessors, circuits, processors, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), memory units, logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth.
  • ASIC application specific integrated circuits
  • PLD programmable logic devices
  • DSP digital signal processors
  • FPGA field programmable gate array
  • Examples of software elements may include software components, programs, applications, computer programs, application programs, system programs, software development programs, machine programs, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computing code, computer code, code segments, computer code segments, words, values, symbols, or any combination thereof.
  • determining whether an example is implemented using hardware elements and/or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints, as desired for a given implementation.
  • the components and features of the devices described above may be implemented using any combination of discrete circuitry, application specific integrated circuits (ASICs), logic gates and/or single chip architectures. Further, the features of the devices may be implemented using microcontrollers, programmable logic arrays and/or microprocessors or any combination of the foregoing where suitably appropriate. It is noted that hardware, firmware and/or software elements may be collectively or individually referred to herein as “logic” or “circuit.”
  • Some examples of the disclosed system may be implemented, for example, using a storage medium, a computer-readable medium or an article of manufacture which may store an instruction or a set of instructions that, when executed by a machine (e g., processor, processing circuit, or microcontroller), may cause the machine to perform a method and/or operations in accordance with examples of the disclosure.
  • a server or database server may include machine readable media configured to store machine executable program instructions.
  • Such a machine may include, for example, any suitable processing platform, computing platform, computing device, processing device, computing system, processing system, computer, processor, or the like, and may be implemented using any suitable combination of hardware, software, firmware, or a combination thereof and utilized in systems, subsystems, components, or sub-components thereof.
  • the various elements of the devices as previously described with reference to the figures above may include various hardware elements, software elements, or a combination of both.
  • hardware elements may include devices, logic devices, components, processors, microprocessors, circuits, processors, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), memory units, logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth.
  • ASIC application specific integrated circuits
  • PLD programmable logic devices
  • DSP digital signal processors
  • FPGA field programmable gate array
  • Examples of software elements may include software components, programs, applications, computer programs, application programs, system programs, software development programs, machine programs, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computing code, computer code, code segments, computer code segments, words, values, symbols, or any combination thereof.
  • determining whether an example is implemented using hardware elements and/or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints, as desired for a given implementation.
  • IP cores may be stored on a tangible, machine readable medium and supplied to various customers or manufacturing facilities to load into the fabrication machines that make the logic or processor.
  • Some examples may be implemented, for example, using a machine-readable medium or article which may store an instruction or a set of instructions that, if executed by a machine, may cause the machine to perform a method and/or operations in accordance with the examples.
  • Such a machine may include, for example, any suitable processing platform, computing platform, computing device, processing device, computing system, processing system, computer, processor, or the like, and may be implemented using any suitable combination of hardware and/or software.
  • the machine- readable medium or article may include, for example, any suitable type of memory unit, memory device, memory article, memory medium, storage device, storage article, storage medium and/or storage unit, for example, memory, removable or non-removable media, erasable or non-erasable media, writeable or re-writeable media, digital or analog media, hard disk, floppy disk, Compact Disk Read Only Memory (CD-ROM), Compact Disk Recordable (CD-R), Compact Disk Rewriteable (CD-RW), optical disk, magnetic media, magneto-optical media, removable memory cards or disks, various types of Digital Versatile Disk (DVD), a tape, a cassette, or the like.
  • CD-ROM Compact Disk Read Only Memory
  • CD-R Compact Disk Recordable
  • CD-RW Compact
  • the instructions may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, encrypted code, and the like, implemented using any suitable high-level, low-level, object-oriented, visual, compiled and/or interpreted programming language.

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Abstract

L'invention concerne des techniques de suivi de rotule assisté par ordinateur. Un procédé comprend la collecte d'un ensemble de premiers points de données et de seconds points de données à partir du fémur, l'ensemble de premiers points de données définissant un mouvement d'une rotule avant et après une opération de remplacement de genou. Le procédé consiste en outre à mapper une première voie et une seconde voie de la rotule, la première voie étant définie par l'ensemble de premiers points de données et la seconde voie étant définie par l'ensemble de seconds points de données. Le procédé comprend en outre la détermination de premiers composants de mouvement de rotule et de seconds composants de mouvement de rotule. Le procédé comprend en outre la comparaison des premiers composants de mouvement de rotule aux seconds composants de mouvement de rotule pour déterminer un écart dans un mouvement de la rotule. Le procédé consiste en outre à déterminer, sur la base de l'écart, une action corrective et à délivrer en sortie une instruction pour effectuer l'action corrective.
PCT/US2025/017488 2024-03-20 2025-02-27 Procédés et systèmes de suivi de rotule Pending WO2025198816A1 (fr)

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US202463567685P 2024-03-20 2024-03-20
US63/567,685 2024-03-20

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080249394A1 (en) * 2007-04-03 2008-10-09 The Board Of Trustees Of The Leland Stanford Junior University Method for improved rotational alignment in joint arthroplasty
US20090264737A1 (en) * 2006-04-07 2009-10-22 Joerg Haechler Patella tracking
US20230039959A1 (en) * 2018-06-21 2023-02-09 Mako Surgical Corp. Patella Tracking
DE102022111282A1 (de) * 2022-05-06 2023-11-09 Aesculap Ag System und Verfahren zur prä-operativen Planung einer Knieendoprothese

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090264737A1 (en) * 2006-04-07 2009-10-22 Joerg Haechler Patella tracking
US20080249394A1 (en) * 2007-04-03 2008-10-09 The Board Of Trustees Of The Leland Stanford Junior University Method for improved rotational alignment in joint arthroplasty
US20230039959A1 (en) * 2018-06-21 2023-02-09 Mako Surgical Corp. Patella Tracking
DE102022111282A1 (de) * 2022-05-06 2023-11-09 Aesculap Ag System und Verfahren zur prä-operativen Planung einer Knieendoprothese

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